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Compare PG Vector and Qdrant 
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At a Glance
Market Segments
Mid-Market (50.0% of reviews)
Small-Business (58.3% of reviews)
Pros & Cons
Not enough data
Not enough data
Entry-Level Pricing
No pricing available
No pricing available
PG Vector
Star Rating
(12)3.8 out of 5
Market Segments
Mid-Market (50.0% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about PG VectorQdrant
Star Rating
(12)4.5 out of 5
Market Segments
Small-Business (58.3% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about QdrantSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Qdrant excels in semantic search capabilities, scoring 9.3, while PG Vector lags behind with a score of 7.7. Reviewers mention that Qdrant's advanced algorithms provide more relevant search results, making it a preferred choice for businesses focused on precision.
- Reviewers mention that Qdrant's indexing data feature is highly rated at 9.5, compared to PG Vector's 7.9. Users on G2 highlight that Qdrant's efficient indexing process significantly reduces query response times, enhancing overall performance.
- Users say that Qdrant offers a superior ease of use rating of 9.1, while PG Vector's score of 7.4 indicates a steeper learning curve. Reviewers mention that Qdrant's intuitive interface allows for quicker onboarding and less training time for new users.
- G2 users report that Qdrant's quality of support is rated at 8.5, which is notably higher than PG Vector's 7.0. Users mention that Qdrant's support team is responsive and knowledgeable, providing timely assistance that enhances user satisfaction.
- Reviewers mention that Qdrant's single-stage filtering for vector databases scores 8.3, outperforming PG Vector's 7.5. Users say that this feature allows for more streamlined data retrieval, which is crucial for applications requiring quick access to specific datasets.
- Users on G2 highlight that both products have a perfect score of 10.0 for product direction, indicating that both Qdrant and PG Vector are seen as forward-thinking solutions. However, reviewers mention that Qdrant's roadmap appears more aligned with user needs, particularly in the realm of AI integration.
Pricing
Entry-Level Pricing
PG Vector
No pricing availableQdrant
No pricing availableFree Trial
PG Vector
No trial information availableQdrant
No trial information availableRatings
Meets Requirements
8.6
11
8.5
11
Ease of Use
7.4
11
9.1
11
Ease of Setup
Not enough data
9.2
11
Ease of Admin
Not enough data
Not enough data
Quality of Support
7.0
11
8.5
9
Has the product been a good partner in doing business?
Not enough data
Not enough data
Product Direction (% positive)
10.0
11
10.0
11
Features by Category
Data Indexing
7.7
8
9.3
10
7.9
8
9.5
10
Filters
8.1
8
8.7
10
7.5
8
8.3
9
Categories
Categories
Shared Categories
PG Vector and Qdrant are categorized as Vector Database
Unique Categories
PG Vector has no unique categories
Qdrant has no unique categories
Reviews
Reviewers' Company Size
PG Vector
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Qdrant
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Information Technology and Services
33.3%
Computer Software
33.3%
Research
8.3%
Mechanical or Industrial Engineering
8.3%
Government Administration
8.3%
Other
8.3%
Manufacturing
16.7%
E-Learning
16.7%
Computer & Network Security
16.7%
Marketing and Advertising
8.3%
Market Research
8.3%
Other
33.3%
Discussions
PG Vector has no discussions with answers
Qdrant has no discussions with answers
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